Review on Exploring Similarity between Two Questions Using Machine Learning

Abstract

Question duplication is the main problem which is based on functionality of allowing users to ask questions . Questions are often answered, and the duplication problem is faced by question and answer sites such as Quora and Reddit, Stack-overflow, and others. Answers are segmented through various iterations of the same question due to question continuity. The aim is to detect the duplicate questions for reducing the redundancy in data. This is a worst experience of users, as the answers get segmented on various versions of the same question, it is bad for writers as well as seekers. Actually this problem also has been noticed on other platforms of Q&A. In this proposed work a simple neural architecture with natural language inference will be used. The approach gathers an attention to pound the problem into sub-problems that helps it to be solved separately, thus making it menially parallelizable. This work is just completely a new pattern, for the solution and it is also possible that it will not provide the complete solution to the problem but may help in increasing the efficiency of the model to predict the duplication's among several question pairs. Question duplication is the serious problem due to the segmentation of answers in various variants of the same question because ofduplication's in these discussion boards. Lastly, As a consequence, there is a lack of a rational search, solution indifference, knowledge separation, and an insufficiency of responses to the questioners. This could be avoided by employing Natural Language Processing as well as Machine Learning, which will help to improve the performance as well.